---
license: apache-2.0
base_model: microsoft/beit-base-patch16-224
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: Karma_3Class_RMSprop_1-e5_10Epoch_Beit-base-patch16_fold5
  results:
  - task:
      name: Image Classification
      type: image-classification
    dataset:
      name: imagefolder
      type: imagefolder
      config: default
      split: test
      args: default
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.8448818098813027
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# Karma_3Class_RMSprop_1-e5_10Epoch_Beit-base-patch16_fold5

This model is a fine-tuned version of [microsoft/beit-base-patch16-224](https://huggingface.co/microsoft/beit-base-patch16-224) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 1.4092
- Accuracy: 0.8449

## Model description

More information needed

## Intended uses & limitations

More information needed

## Training and evaluation data

More information needed

## Training procedure

### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 1e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Accuracy |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 0.434         | 1.0   | 2468  | 0.4027          | 0.8307   |
| 0.321         | 2.0   | 4936  | 0.3800          | 0.8422   |
| 0.2658        | 3.0   | 7404  | 0.3919          | 0.8538   |
| 0.1883        | 4.0   | 9872  | 0.5137          | 0.8496   |
| 0.1083        | 5.0   | 12340 | 0.6774          | 0.8501   |
| 0.1819        | 6.0   | 14808 | 0.9184          | 0.8469   |
| 0.1208        | 7.0   | 17276 | 1.1502          | 0.8448   |
| 0.1339        | 8.0   | 19744 | 1.3133          | 0.8418   |
| 0.0217        | 9.0   | 22212 | 1.3895          | 0.8434   |
| 0.0057        | 10.0  | 24680 | 1.4092          | 0.8449   |


### Framework versions

- Transformers 4.35.0
- Pytorch 2.1.0
- Datasets 2.14.6
- Tokenizers 0.14.1